‘Narrative’ information concerns in general the account of some real-life or fictional story (a ‘narrative’) involving concrete or imaginary ‘personages’. In this article we deal with (multimedia) nonfictional narratives of an economic interest. This means, first, that we are not concerned with all sorts of fictional narratives that have mainly an entertainment value, and represent an imaginary narrator’s account of a story that happened in an imaginary world: a novel is a typical example of fictional narrative. Secondly, our ‘nonfictional narratives’ must have an economic value: they are then typically embodied into corporate memory documents, they concern news stories, normative and legal texts, medical records, intelligence messages, surveillance videos or visitor logs, actuality photos and video fragments for newspapers and magazines, eLearning and multimedia Cultural Heritage material, etc. Because of the ubiquity of these ‘narrative’, ‘dynamic’ resources, it is particularly important to build up computer-based applications able to represent and to exploit in a general, accurate, and effective way the semantic content – i.e., the key ‘meaning’ – of these resources.
‘Narratives’ represent presently a very ‘hot’ domain. From a theoretical point of view, they constitute the object of a full discipline, the ‘narratology’, whose aim can be defined as that of producing an in-depth description of the ‘syntactic/semantic structures’ of the narratives, i.e., the narratologist is in charge of dissecting narratives into their component parts in order to establish their functions, their purposes and the relationships among them. A good introduction to the full domain is (Jahn, 2005).
Even if narratology is particularly concerned with literary analysis (and, therefore, with ‘fictional’ narratives), these last years some of its varieties have acquired a particular importance also from a strict Artificial Intelligence (AI) and Computer Science (CS) point of view. Leaving apart the old dream of generating fictions by computer, see (Mehan, 1977) and, more recently, (Callaway and Lester, 2002), we can mention here two new disciplines, ‘storytelling’ and ‘eChronicles’, that are of interest from both a nonfictional narratives and a AI/CS point of view.
Storytelling – see, e.g., (Soulier, 2006) – concerns in general the study of the different ways of conveying ‘stories’ and events in words, images and sounds in order to entertain, teach, explain etc. Digital Storytelling deals in particular with the ways of introducing characters and emotions in the interactive entertainment domain, and concerns then videogames, massively multiplayer online games, interactive TV, virtual reality etc., see (Handler Miller, 2004). Digital Storytelling is, therefore, related to another, computer-based variant of narratology called Narrative Intelligence, a sub-domain of AI that explores topics at the intersection of Artificial Intelligence, media studies, and human computer interaction design (narrative interfaces, history databases management systems, artificial agents with narrative structured behaviour, systems for the generation and/or understanding of histories/narratives etc.), see (Mateas and Sengers, 2003).
An eChronicle system can be defined in short as way of recording, organizing and then accessing streams of multimedia events captured by individuals, groups, or organizations making use of video, audio and other sensors. The ‘chronicles’ gathered in this way may concern any sort of ‘narratives’ from meeting minutes to football games, sales activities, ‘lifelogs’ obtained from wearable sensors, etc. The technical challenges concern mainly the ways of aggregating the events into coherent ‘episodes’ making use of domain models as ontologies, and providing then access to this sort of material to the users at the required level of granularity. Note that exploration, and not ‘normal’ querying, is the predominant way of interaction with the chronicle repositories; more details can be found, e.g., in (Güven, Podlaseck and Pingali, 2005), (Westermann and Jain, 2006).
Key Terms in this Chapter
Connectivity Phenomena: In the presence of several, logically linked elementary events, this term denotes the existence of a global ‘narrative’ information content that goes beyond the simple addition of the information conveyed by the single events. The connectivity phenomena are linked with the presence of logico-semantic relationships like causality, goal, co-ordination and subordination etc.
Nonfictional Narrative of an Economic Interest: In this case, the personages are ‘real characters’, and the narrative happens in the real world. Moreover, the narratives are now embodied in multimedia documents of an economic interest corporate memory documents, news stories, normative and legal texts, medical records, intelligence messages, surveillance videos or visitor logs, etc.
Examples of n-ary Languages: ‘Historical’ examples of n-ary languages are Ceccato’s ‘correlations’, Schank’s Conceptual Dependency theory, many Semantic Networks proposals, etc. Current n-ary systems are, e.g., Topic Maps, Sowa’s Conceptual Graphs, Lenat’s CYC, etc. None of them are able to satisfy completely the requirements for an ‘intelligent’ representation and management of nonfictional narrative information.
‘Binary’ Languages vs. n-ary Languages: Binary languages (like RDF and OWL) are based on the classical ‘attribute – value’ model they are called ‘binary’ because, for them, a property can only be a binary relationship, linking two individuals or an individual and a value. They cannot be used to represent in an accurate way the narratives that ask in general, on the contrary, for the use of n-ary knowledge representation languages.
Narratology: Discipline that deals with narratives from a theoretical point of view. Sub-classes of narratology that have a ‘computational’ interest are, e.g., Storytelling, Narrative Intelligence and the eChronicle systems.
Core Format of a Complete Solution for Representing Narratives: Formally, an n-ary structure able to represent the ‘essential meaning’ of an ‘elementary event’ can be described as(Li (Pj (R1 a1) (R2 a2) … (Rn an))) where Li is the symbolic label identifying the particular formalized event, P is the conceptual predicate, Rk is the generic role and ak the corresponding argument.
Narrative Information: Concerns in general the account of some real-life or fictional story (a ‘narrative’) involving concrete or imaginary ‘personages’.